Train operation plan coordination optimization method, device, equipment and storage medium

Abstract

The invention provides a train operation plan coordinated optimization method, device and equipment and a storage medium, and relates to the technical field of marshalling station group skylight scheme optimizing.The method comprises the steps that the preset maintenance duration is divided into a plurality of skylights based on the traffic flow of a marshalling station, and a plurality of regional skylights are obtained; acquiring basic data of a marshalling station; constructing an optimization model based on the basic data and the plurality of regional skylights to obtain a multi-objective optimization model; based on a preset constraint function in the multi-target optimization model, adjusting the basic data to obtain target data; and performing corresponding adjustment on the train operation plan based on the target data. According to the method, the optimization model is constructed, and the skylight scheme and the train operation plan are optimized, so that the relative optimization of the two objectives of the minimum time of the traffic flow in the station and the combination of the traffic flow passing through the same area skylight as much as possible is realized, the skylight cashing rate is improved, the operation efficiency of the marshalling station is further improved, and the operation safety of the marshalling station is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of marshaling group skylight scheme optimization, and in particular to a train operation plan coordination optimization method, device, equipment and storage medium. Background Art

[0002] The skylight of a marshalling yard is the time reserved for construction and maintenance operations to carry out maintenance and repair of railway equipment, ensure driving safety and personal safety, and achieve transportation tasks while ensuring operational safety. When the skylight is opened in the marshalling yard, vehicles cannot pass through the maintenance area, which conflicts with the marshalling yard's implementation of transportation tasks. As the marshalling yard's transportation tasks become heavier, the marshalling yard's equipment wears out more, and the marshalling yard's maintenance needs increase. The heavier transportation tasks increase the utilization rate of various facilities and equipment in the marshalling yard, but the increased maintenance needs require more frequent and longer skylights, and the contradiction between the marshalling yard's transportation tasks and the skylight plan intensifies. Therefore, coordinating and optimizing the marshalling yard's skylight plan and train operation plan can effectively alleviate the contradiction between transportation and maintenance and improve railway production efficiency and management level. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device, equipment and storage medium for coordinating and optimizing train operation plans to improve the above problems. In order to achieve the above objectives, the technical solutions adopted by the present invention are as follows:

[0004] In a first aspect, the present application provides a method for coordinating and optimizing a train operation plan, comprising:

[0005] Based on the traffic volume of the marshalling yard, the preset maintenance time is divided into multiple skylights to obtain multiple regional skylights;

[0006] Obtaining basic data of the marshalling yard, the basic data including the train operation plan, all operations to be completed and corresponding time thresholds;

[0007] An optimization model is constructed based on the basic data and multiple regional skylights to obtain a multi-objective optimization model, wherein the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function;

[0008] Based on the constraint functions preset in the multi-objective optimization model, the basic data is adjusted to obtain target data, where the target data is data that satisfies each constraint function in the multi-objective optimization model;

[0009] The train operation plan is adjusted accordingly based on the target data.

[0010] In a second aspect, the present application also provides a train operation plan coordination optimization device, comprising:

[0011] A first obtaining unit is used to divide the preset maintenance time into a plurality of skylights based on the vehicle flow of the marshaling yard to obtain a plurality of regional skylights;

[0012] An acquisition unit, used to acquire basic data of a marshalling yard, wherein the basic data includes a train operation plan, all operations to be completed and corresponding time thresholds;

[0013] A second obtaining unit is used to construct an optimization model based on the basic data and multiple regional skylights to obtain a multi-objective optimization model, wherein the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function;

[0014] A first adjustment unit, configured to adjust the basic data based on a constraint function preset in the multi-objective optimization model to obtain target data, wherein the target data is data satisfying each constraint function in the multi-objective optimization model;

[0015] The second adjustment unit is used to make corresponding adjustments to the train operation plan based on the target data.

[0016] In a third aspect, the present application also provides a train operation plan coordination optimization device, comprising:

[0017] Memory for storing computer programs;

[0018] A processor is used to implement the steps of the train operation plan coordination optimization method when executing the computer program.

[0019] In a fourth aspect, the present application also provides a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method based on coordinated optimization of train operation plans are implemented.

[0020] The beneficial effects of the present invention are:

[0021] The present invention achieves the relative optimality of the two goals of minimizing the time that vehicles spend in the station and concentrating the vehicles as much as possible through the skylight combination in the same area by constructing an optimization model, optimizing the skylight scheme and the train operation plan, thereby improving the skylight realization rate, further improving the operating efficiency of the marshalling yard, and ensuring the operational safety of the marshalling yard.

[0022] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 It is a flow chart of the train operation plan coordination optimization method described in an embodiment of the present invention;

[0025] Figure 2 It is the chromosome coding diagram of the train described in the embodiment of the present invention;

[0026] Figure 3 It is the chromosome coding diagram of the self-compiled departure train described in the embodiment of the present invention;

[0027] Figure 4 is the chromosome coding diagram of the through train described in the embodiment of the present invention;

[0028] Figure 5 It is a structural schematic diagram of the train operation plan coordination and optimization device described in an embodiment of the present invention;

[0029] Figure 6 It is a schematic diagram of the structure of the train operation plan coordination and optimization equipment described in an embodiment of the present invention.

[0030] Markings in the figure: 10, first obtaining unit; 20, obtaining unit; 30, second obtaining unit; 40, first adjusting unit; 50, second adjusting unit;

[0031] 800. Train operation plan coordination and optimization equipment; 801. Processor; 802. Memory; 803. Multimedia component; 804. I / O interface; 805. Communication component. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0034] Embodiment 1:

[0035] This embodiment provides a method for coordinating and optimizing a train operation plan.

[0036] See also Figure 1 , the figure shows that the method includes step S10, step S20, step S30, step S40 and step S50.

[0037] Step S10. Divide the preset maintenance time into multiple skylights based on the traffic volume of the marshaling yard to obtain multiple regional skylights;

[0038] Specifically, the marshaling yard is divided into parallel approach areas, busy areas and junction areas, and windows are divided in each area. Among them, the parallel approach area is divided into multiple different regional windows. When a window is opened in a certain area, there are still other parallel approaches for trains to run, reducing the impact of the window opening on the marshaling yard; the busy area has a high operation frequency, and once a window is opened, it will have a great impact on the entire transportation operation. It is divided into a separate regional window, and maintenance work is carried out in the busy area at one time to minimize the impact of opening the window in the busy area. For example, the marshaling yard is busy with hump operations, consider dividing the hump and push line and other related areas into a separate regional window, use the time with less traffic to carry out maintenance, and reduce the impact of hump maintenance on the operation efficiency of the marshaling yard; based on the impact of junctions, regional windows based on junctions are divided.

[0039] Step S20. Obtain basic data of the marshalling yard, which includes the train operation plan, all operations to be completed and the corresponding time threshold;

[0040] Specifically, statistics are collected on parallel routes, including parallel routes for through trains and parallel routes for arrival and departure trains, and statistics are collected on the number of yards and regional skylights they pass through; statistics are collected on the current vehicles in the marshalling yard and the traffic data for the day, including the vehicle content and location of each yard, through train information (train number, arrival time), arrival and departure train information (train number, arrival time, marshalling content), and self-organized departure train flow distribution plans (train number, marshalling content, and vehicle source); and standardized descriptions of arrival technical operations, peak-pushing technical operations, shunting technical operations, and through train running operation times.

[0041] Step S30. construct an optimization model based on the basic data and multiple regional skylights to obtain a multi-objective optimization model, the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function;

[0042] Specifically, the traffic flow is concentrated as much as possible through the skylight combination in the same area, and the total time period of each skylight area is minimized to construct the first objective function:

[0043] Specifically, step S30 specifically includes step S31, step S32, step S33 and step S34:

[0044] Step S31. Construct a first objective function based on the occupancy time of the arrival train in the regional skylight, the occupancy time of the self-organized departure train in the regional skylight, and the occupancy time of the through train in the regional skylight;

[0045] Specifically, step S31 specifically includes step S311, step S312, step S313, step S314, step S315 and step S316:

[0046] Step S311. The train operation plan includes multiple routes, and the routes are represented by one or more of the following: arrival track occupancy status, push line occupancy status, release line occupancy status, departure track occupancy status, outer line occupancy status, and departure through track occupancy status, including:

[0047] Step S312: Based on the arrival track occupation state, the push line occupation state and the first decision variable, a first function is obtained, where the first decision variable is used to characterize whether the approach corresponding to the arrival track and the push line belongs to the regional skylight;

[0048] Step S313. Based on the departure track occupation state, the release line occupation state and the second decision variable, a second function is obtained, where the second decision variable is used to characterize whether the route corresponding to the departure track and the release line belongs to the regional skylight;

[0049] Step S314: Based on the arrival track occupation state, the outer line occupation state and the third decision variable, a third function is obtained, where the third decision variable is used to characterize whether the approach corresponding to the arrival track and the outer line belongs to the regional skylight;

[0050] Step S315. Based on the occupation status of the departure yard through track, the occupation status of the outer line and the fourth decision variable, a fourth function is obtained, where the fourth decision variable is used to characterize whether the routes corresponding to the departure yard through track and the outer line belong to the regional skylight;

[0051] Step S316. Sum the first function, the second function, the third function and the fourth function to obtain a first objective function;

[0052] Specifically, the first objective function is:

[0053]

[0054] Among them, f1 is the first objective function; P j is the regional skylight combination index; R is the route set; R i is the route set index; s D is the arrival track index; H Push line index; s P Index of the release line; M is the departure track index; s is the outer line index; M′ It is the direct track index of the departure field; Whether the access road belongs to a certain area skylight combination; R(D,t,s D ,h) is the occupancy status of the track at the arrival site at time t on the hth day; R(H,t,s H ,h) is the occupancy status of the push line at time t on the hth day; R(P,t,s P ,h) is the occupancy status of the release line at time t on the hth day; R(M,t,s M ,h) is the occupancy status of the departure track at time t on the hth day; R(S,t,s S ,h) is the occupancy status of the outer line at time t on the hth day; R(M',t,s M′ ,h) is the occupancy status of the departure field through track at time t on the hth day; n i is the number of elements in the route set; n j is the number of elements in the skylight combination set; n D is the number of tracks arriving at the site; n H is the number of push lines; n P is the number of release lines; n M is the number of departure tracks; n S is the number of outer wires; n M′ is the number of direct tracks; D is the arrival track; H is the push line; P is the release line; M is the departure track; S is the outer line; M' is the direct track; T is the decision cycle.

[0055] When the access road belongs to a certain area skylight combination, The value is 1, otherwise it is 0. When occupied, the corresponding occupancy status value is 1, otherwise it is 0.

[0056] Step S32. Construct a second objective function based on the travel time of the arriving and departing trains at the marshaling yard, the travel time of the self-organized and departing trains at the marshaling yard, and the travel time of the through trains at the marshaling yard;

[0057] Specifically, the travel times of the arriving train, the self-organized departure train and the through train are respectively represented by their respective route start time and route end time and summed to construct the second objective function.

[0058] Specifically, step S32 specifically includes step S321, step S322, step S323 and step S324:

[0059] Step S321. Calculate the difference between the arrival time of each train at the marshaling yard and the disassembly completion time to obtain multiple fifth functions;

[0060] Step S322. Calculate the difference between the travel time of each self-organized departure train and the time of leaving the marshaling yard to obtain multiple sixth functions;

[0061] Step S323. Calculate the difference between the arrival time and the departure time of each through train at the marshaling yard to obtain multiple seventh functions;

[0062] Step S324. Sum the plurality of fifth functions, the plurality of sixth functions and the plurality of seventh functions to obtain a second objective function;

[0063] Specifically, the second objective function is:

[0064]

[0065] Among them, f2 is the second objective function; The time when the train dismantling operation starts; The time when the dismantling train ends occupying the arrival track; The time when the self-organized departure train starts to occupy the departure track; It is the time when the self-organized departure train starts to move from the shunting yard to the departure yard track; The time when technical operations for through trains begin; The time when the through train ends its occupation of the arrival track; The time when the train that arrives on the hth day starts to enter the route; The time when the train dismantling is completed on the hth day; The starting time of the self-organized train route on day h; The departure time of the self-organized train on day h from the marshaling yard; The departure time of the through train from the marshaling yard on the hth day; is the arrival time of the through train at the marshaling yard on the hth day; m 1 is the number of dismantled trains; m 2 is the number of self-organized departure trains; m 3 is the number of through trains; T is the decision cycle; i is the number of the arriving and departing trains; k is the number of the self-compiled departure train; and p is the number of the through train.

[0066] Step S33. Construct multiple constraint functions based on the basic data to obtain multiple constraint functions;

[0067] Specifically, step S33 specifically includes step S331, step S332, step S333, step S334 and step S335:

[0068] Step S331. Based on the operation logic of the arrival and departure trains, the operation logic of the self-compiled departure trains and the operation logic of the through trains, multiple operation constraint functions are constructed;

[0069] Specifically, the operation sequence of the arriving train is: track access operation, peak pushing operation and shunting operation. The expression of the arriving train operation constraint function is as follows:

[0070]

[0071] in, To understand the arrival status of the train; It is the peak pushing operation state of the arriving and discharging trains; The dismantling operation status of the arriving train; m 1 is the number of trains arriving or leaving; T is the decision cycle; i is the train number arriving or leaving;

[0072] It is a 0-1 variable, which is 1 if the arriving train performs the arrival technical operation, otherwise it is 0; It is a 0-1 variable, which is 1 if the train is performing peak pushing operation, otherwise it is 0; It is a 0-1 variable, which is 1 if the train is ready for dismantling, and 0 otherwise.

[0073] The operation sequence of the self-organized departure train f(k,h) is: marshaling operation and departure operation. The operation constraint function expression of the self-organized departure train is as follows:

[0074]

[0075] in, The departure technical status of the self-organized departure train; It is the running route status of the self-compiled departure train; The self-organized departure train marshaling operation is completed; m 2 is the number of self-organized departure trains; k is the number of self-organized departure trains; T is the decision cycle;

[0076] It is a 0-1 variable, which is 1 if the self-organized originating train is carrying out the departure technology, otherwise it is 0; It is a 0-1 variable, which is 1 if the self-organized originating train is on the route, otherwise it is 0; It is a 0-1 variable, and it is 1 if the self-organized departure train completes the marshaling operation.

[0077] The operation sequence of the through train z(p,h) is: running from the arrival yard to the outer line, running from the outer line to the departure yard through track and technical operations. The through train operation constraint function expression is as follows:

[0078]

[0079] in, The through train is in departure status; The through train is running from the outer line to the departure track; It is the state for through trains to move from the arrival track to the outer track; The through train arrives; m 3 is the number of through trains; T is the decision cycle; p is the number of the through train;

[0080] is a 0-1 variable, 1 if a through train departs, otherwise 0; It is a 0-1 variable. If the through train runs from the outer line to the departure track, it is 1, otherwise it is 0. It is a 0-1 variable, which is 1 if the through train runs from the arrival track to the outer track, otherwise it is 0; It is a 0-1 variable, which is 1 if the through train arrives at the arrival track, otherwise it is 0.

[0081] Through trains involve entering and leaving the outer line. Although the capacity of the outer line is considered infinite, the through train that enters the outer line first needs to leave the outer line first. Therefore, the operation constraint function expression of the through train is:

[0082] t(p-1,Z l ,h)≤t(p,Z l ,h)

[0083] Among them, t(p-1,Z l ,h) is the departure time of the through train No. p-1 on the hth day from the outer line to the departure track; t(p,Z l ,h) is the departure time of the pth through train on the hth day when it runs along the outer line to the departure track; p is the number of the through train.

[0084] Step S332. Based on the number of tracks at the departure yard, the number of tracks at the arrival yard, the disassembly and shunting capacity, the number of push lines, the number of release lines, the shunting yard capacity and the marshaling and shunting capacity, multiple resource capacity constraint functions are constructed;

[0085] Specifically, at any time there are at most n DA train is connected to the arrival yard, and the capacity constraint of the access track of the arrival yard is as follows:

[0086]

[0087]

[0088] in, To understand the arrival status of the train; is the arrival state of the through train; R(D,t,s D ,h) is the occupancy status of the track at the arrival site at time t on the hth day; The time when the train starts occupying the track on the hth day; The time when the track occupation ends on the hth day for the train to arrive; The time when the through train starts occupying the track on the hth day; The time when the through train ends occupying the track on the hth day; t s is the starting time of the decision cycle within the day; t e is the end time of the decision cycle within the day; T is the decision cycle; D is the arrival track; i is the number of the train arriving; D is the arrival track; n D is the number of tracks arriving at the site, s D ∈n D .

[0089] At any time, there are at most n H The push line is occupied. For the same push line, only one train can occupy it at the same time. The push line capacity constraint is as follows:

[0090]

[0091] in, The peak pushing operation state of the arriving and discharging trains; R(H,t,s H ,h) is the push line R(H,s H ,h) occupancy status; The end time of the peak pushing operation for the train arriving on the hth day; is the starting time of the peak push operation of the through train on the hth day; t s is the starting time of the decision cycle within the day; t e is the end time of the decision cycle within the day; T is the decision cycle; i is the number of the train arriving and departing; H is the push line; n H is the number of push lines, s H ∈n H ; H is the push line.

[0092] At any time, there are at most n BThe dismantling train is called. In addition to participating in train dismantling, the dismantling train also participates in the peak pushing operation. The dismantling train capacity constraints are as follows:

[0093]

[0094] in, It is the peak pushing operation state of the arriving and discharging trains; is the dismantling operation status of the arriving train; R(B,t,s B ,h) is the hump disassembly and adjustment machine R(B,s B ,h) occupancy status, The end time of the peak pushing operation for the train arriving on the hth day; The starting time of the peak push operation for the through train on the hth day; The time when the dismantling operation of the train is completed on the hth day; is the start time of dismantling operation of through train on day h; t s is the starting time of the decision cycle within the day; t e is the end time of the decision cycle within the day; T is the decision cycle; i is the number of the arriving train; n B is the number of hump disassembly and adjustment, s B ∈n B ; B is for disassembly and adjustment of the machine.

[0095] At any time, there are at most n P The stock release line is occupied, and the release line capacity constraints are as follows:

[0096]

[0097] Among them, R(P,t,s P ,h) is the release line R(P,s P ,h) occupancy status; It is in the state of self-sliding line occupancy; The time when the self-organized departure train starts to occupy the shunting line; The time when the self-organized departure train ends occupying the shunting line; t s The starting time of the decision cycle of the self-organized departure train on that day; t e The day when the self-organized departure train is set is the end time of the decision cycle; T is the decision cycle; k is the number of the self-organized departure train; n P is the number of release lines, s P ∈n P ; P is the release line.

[0098] At any time, there are at most n FA marshaling train is assembled for marshaling operation. Since the marshaling locomotive needs to send the self-assembled departure train to the departure yard after the train marshaling operation is completed, the marshaling locomotive will be occupied by the train from the start of the train marshaling operation to the start of the departure technical operation. The capacity constraint of the marshaling locomotive is as follows:

[0099]

[0100] in, The self-organized departure train marshaling operation is completed; It is the running route status of the self-compiled departure train; The start time of marshaling of self-organized departure trains; The time when the self-organized departure train is completed; The time when the self-organized departure train starts to travel on the route; The time when the self-organized departure train ends its route; t s The starting time of the decision cycle of the self-organized departure train on that day; t e The day when the self-organized departure train is set is the end time of the decision cycle; T is the decision cycle; k is the number of the self-organized departure train; n F is the number of trains to be dispatched, s F ∈n F ; F is the marshaling and adjustment machine.

[0101] At any time, there are at most n M The departure track is occupied, and the departure track capacity constraints are as follows:

[0102]

[0103] in, The departure technical status of the self-organized departure train; is the technical status of the through train departure; R(M,t,s M ,h) is the departure track R(M,s M ,h) occupancy status; The time when the self-organized departure train starts to travel on the route; The time when the self-compiled departure train ends its route; The time when technical operations for through trains begin; is the time when the through train leaves the through track; t s is the starting time of the decision cycle within the day; t e The end time of the decision cycle within the day; T is the decision cycle; n M is the number of departure tracks, s M ∈n M ; M is the departure track; p is the through train number; k is the self-compiled departure train number;.

[0104] The number of vehicles in the marshaling yard must not exceed the marshaling yard capacity, and the constraints are as follows:

[0105]

[0106] Among them, m 1 is the number of trains arriving and departing; m 2 The number of self-organized departure trains; The start time of marshaling of self-organized departure trains; is the end time of the peak pushing operation of the arriving and discharging train; q is the vehicle flow direction or vehicle type attribute contained in the arriving and discharging train / train formation; α is the number of vehicle flow directions or vehicle type attributes contained in the arriving and discharging train / train formation; c(W,i,k,h) is the capacity of R(W,i,q,h); R(W,i,q,h) is the vehicle flow with attribute q contained in the arriving and discharging train; t s is the starting time of the decision cycle within the day; t e is the end time of the decision cycle within the day; T is the decision cycle; i is the number of the arriving train; k is the number of the self-compiled departure train; W is the traffic flow.

[0107] Step S333. Based on the connection status between the arrival track and the push line, the connection status between the release line and the departure track, the connection status between the arrival track and the outer line, and the connection status between the outer line and the departure track, a resource connection constraint function and a resource occupancy status constraint function are constructed;

[0108] Specifically, the resource occupancy state constraint function includes:

[0109] When the train is transferred from the arrival track to the push track, the arrival track is gradually vacated as the train is pushed. However, in order to ensure safety, the time when the train ends its occupation of the arrival track is equal to the time when it starts to run on the route. Assuming that the train stays at R(D,t,s D ,h) track, that is, the track at the arrival yard is occupied until the train starts to move along the route, and the corresponding constraint function is:

[0110]

[0111]

[0112] in, To understand the arrival status of the train; To understand the running status of the train from the arrival track to the push track; The time when the track occupation by the arriving train ends; is the time when the arriving train starts to move; R(D,t,s D ,h) is the stock track R(D,s D ,h) occupancy status; m1 is the number of arriving trains; The time when the technical operation of the arriving train starts; is the end time of occupied track; T is the decision cycle; i is the number of the arriving train; D is the arrival track; n D is the number of tracks arriving at the site, s D ∈n D .

[0113] Under the double push and double slide method, the train arriving at the dismantling station does not need to wait for the peak. The end time of the train occupying the route is equal to the start time of the push peak. Assuming that the train arriving at the dismantling station is selected at the first Arrival track to Push line v i route, that is, the route is occupied until the train starts to push the peak, and the corresponding constraint function is:

[0114]

[0115]

[0116] in, To understand the running status of the train from the arrival track to the push track; It is the peak pushing operation state of the arriving and discharging trains; The starting time of the peak pushing operation for arriving and discharging trains; is the track R(D,s D ,h) and push line R(H,s H ,h)Under the connection condition, the vth i The paths involve resource occupation status; m 1 is the number of arriving trains; The time when the arriving train starts to move on route; is the time when the train arrives and leaves; T is the decision cycle; i is the train number; D is the track at the arrival yard; n D is the number of tracks arriving at the site, s D ∈n D ;n H is the number of push lines, s H ∈n H ; H is the push line.

[0117] Under the double push and double slide method, the train arriving at the dismantling does not need to wait for the peak but dismantles directly. Assuming that the train arriving at the dismantling is at R(H,t,s H ,h) Pushing the peak line pushes the peak, so the peak pushing operation and dismantling operation constraints of the dismantling train are as follows:

[0118]

[0119]

[0120] in, It is the peak pushing operation state of the arriving and discharging trains; The train is in dismantling operation state; The time when the dismantling operation of the train is completed; is the time when the unloading operation of the arriving train starts; R(H,t,s H ,h) is the push line R(H,s H ,h) occupancy status; m 1 is the number of arriving trains; The time when the train sliding operation is completed; is the starting time of the peak pushing operation for the arriving and discharging trains; T is the decision cycle; n H is the number of push lines, s H ∈n H ; H is the push line; i is the number of the arriving train.

[0121] When the arriving train is disassembled, the traffic resources required for the self-organized departure train are generated. In daily work, traffic resources should be generated as the train is disassembled. In order to ensure safety and facilitate scheduling, it is assumed that the vehicles are uniformly disassembled to each track at the moment the train is disassembled. The corresponding constraint function is:

[0122]

[0123]

[0124] in, The train is in dismantling operation state; is the time when the sliding operation of the train is completed; R(W,t,i,h) is the disassembly status of the train at time t on the hth day; m 1 is the number of arriving and discharging trains; T is the decision cycle; W is the traffic flow; i is the number of the arriving and discharging train.

[0125] After the self-organized departure train is assembled, it is pushed to the departure yard by the shunting locomotive. As the train is sent to the departure yard, the shunting yard tracks are gradually vacated. To ensure safety and facilitate dispatching, it is assumed that the shunting yard tracks are occupied during the train pushing process until it is pushed to the departure yard and the departure technical operation begins. Assuming that the self-organized departure train occupies the shunting track R(P,t,s P ,h), that is, the track in the shunting yard is occupied until the departure train starts to move. The corresponding constraint function is:

[0126]

[0127]

[0128] in, It is the running route status of the self-compiled departure train; The self-organized departure train marshaling operation is completed; The time when the self-organized departure train is completed; The time when the self-organized departure train starts to travel; R(P,t,s P ,h) is the release line R(P,s P ,h) occupancy status; The time when the self-organized departure train starts to occupy the shunting line; The time when the self-organized departure train occupies the shunting line ends; m 2 is the number of self-organized departure trains; T is the decision cycle; k is the number of self-organized departure trains; n P is the number of release lines, s P ∈n P ; P is the release line.

[0129] The route of the self-organized departure train is occupied until the departure technical operation starts. Assuming that the self-organized departure train is on the shunting line and departure track Select the vth j The corresponding constraint function is:

[0130]

[0131]

[0132] in, It is the running route status of the self-compiled departure train; The departure technical status of the self-organized departure train; The time when the self-compiled departure train ends its route; The time when the self-organized departure train starts to occupy the track; is the release line R(P,s P ,h) and departure track R(M,s M ,h)Under the connection condition, the vth j The approach involves the resource being occupied state; The time when the self-organized departure train starts to travel on the route; The time when the self-organized departure train ends its route; m 2 is the number of self-organized departure trains; T is the decision cycle; k is the number of self-organized departure trains; n P is the number of release lines, s P ∈n P ; P is the release line; n M is the number of departure tracks, s M ∈n M ; M is the departure track; p is the through train number.

[0133] When a through train goes from the arrival yard to the outer line, the arrival yard track R(D,t,s D ,h) The occupied state ends when the through train starts to move along the route. The corresponding constraint function is:

[0134]

[0135]

[0136] in, The through train occupies the arrival track; It is the state for through trains to move from the arrival track to the outer track; The time when the through train ends its occupation of the track; The time when the through train starts to move from the arrival track to the outer track; R(D,t,s D ,h) is the track R(D,s D ,h) occupancy status; The time when the through train starts occupying the track; The time when the through train ends occupying the track; m 3 is the number of through trains; T is the decision cycle; p is the number of through trains; D is the track of the arrival yard; n D is the number of tracks arriving at the site, s D ∈n D .

[0137] When the through train arrives at the outer line, it is assumed that the through train selects the vth k The route is occupied until the through train runs to the outer line. The corresponding constraint function is:

[0138]

[0139]

[0140] in, It is the state for through trains to move from the arrival track to the outer track; It is the time when the through train starts to run from the arrival track to the outer track; It is the time when the through train leaves the arrival track and enters the outer line; is the track R(D,s D ,h) and the outer envelope line R(S,s S ,h)Under the connection condition, the vth k The routes involve resource occupation status; T is the decision cycle; p is the through train number; D is the arrival track; n D is the number of tracks arriving at the site, s D ∈nD ;n S is the number of outer wires, s S ∈n S ; S is the outer cable.

[0141] When a through train goes from the outer line to the specific track of the departure yard, the outer line to the specific track of the departure yard is v l The route is occupied until the through train runs to the specific track of the departure yard:

[0142]

[0143]

[0144] in, The through train is running from the outer line to the departure track; is the outer envelope R(S,s S ,h) and the departure field specific track R(M',s M′ ,h)Under the connection condition, the vth l The paths involve resource occupation status; m 3 is the number of through trains, The time when the through train starts to run from the outer line to the departure track; is the time when the through train arrives at the track, T is the decision cycle; n M′ is the number of through channels, s M′ ∈n M′ ; M' is the through track; p is the through train number; n S is the number of outer wires, s S ∈n S ; S is the outer cable.

[0145] When a through train goes from the outer line to the specific track of the departure yard, the specific track of the departure yard The occupied state ends until the through train departs, and the corresponding constraint function is:

[0146]

[0147]

[0148] in, The through train is running from the outer line to the departure track; The time when the through train starts to run from the outer line to the departure track; The time it takes for a through train to arrive at the track; m 3 is the number of through trains; T is the decision cycle; n M′ is the number of through channels, s M′ ∈n M′; M' is the through track; p is the through train number.

[0149] Specifically, the resource connectivity constraint functions include:

[0150] Arrival and dispatching trains need to be allocated arrival yard tracks, routes from arrival yard tracks to push lines, and push line resources; self-organized departure trains need to be allocated shunting yard tracks, routes from shunting lines to departure yard tracks, and departure yard track resources; through trains need to be allocated arrival yard tracks, routes from arrival yard tracks to external lines, routes from external lines to departure yard tracks, and departure yard tracks.

[0151] If the machine is dismantled and adjusted at time t Through the v i Arrival track To push line The route is pushed to the solution train, and the corresponding constraint function is:

[0152]

[0153]

[0154] in, To arrive at the track; For push line; When the arrival track R(D,sD,h) and the push line R(H,sH,h) are connected at time t, the vi route involves the resource occupied state; To dismantle and adjust the machine; B is the number of dismantling and adjustment machines; m 6 is the track connected to the arrival site at time t (D, s D ,h) and push line R(H,s H ,h) Total number of routes; The time to start walking; is the end time of the route; i is the number of the arriving train; D is the arrival track; n D is the number of tracks arriving at the site, s D ∈n D ;n H is the number of push lines, s H ∈n H ; H is the push line.

[0155] If at time t the train is dispatched by the marshaling group Through the v j Release line To departure track If the route pushes the self-organized departure train, the corresponding constraint function is:

[0156]

[0157]

[0158] in, To release the line; The departure track; To adjust the locomotive for marshaling; When the release line R(P,sP,h) and the departure track R(M,sM,h) are connected at time t, the vth j The paths involve resource occupation status; n F is the number of train sets; m 7 is the connecting release line R(P,s P ,h) and departure track R(M,s M ,h) Total number of routes; The time when the walking route starts; The end time of the walking route; M ∈n M ; M is the departure track; p is the through train number; k is the self-compiled departure train number; n P is the number of release lines, s P ∈n P ; P is the release line.

[0159] If you want a direct train p At time t, from the arrival track Go to Outsourcing Line The corresponding constraint function is:

[0160]

[0161]

[0162] in, To arrive at the track; For outsourcing line; is the track R(D,s D ,h) and the outer envelope line R(S,s S ,h)Under the connection condition, the vth k The paths involve resource occupation status; m 8 is the track connected to the arrival site at time t (D, s D ,h) and the outer envelope line R(S,s S ,h) Total number of routes; The time when the vehicle starts to move from the arrival track to the outer line; The time when the train leaves the arrival track and enters the outer line; p is the through train number; D is the arrival track; n D is the number of tracks arriving at the site, s D ∈nD ;n S is the number of outer wires, s S ∈n S ; S is the outer cable.

[0163] If you want a direct train p At time t, the external line Transfer to the departure track, then transfer to the specific track The corresponding constraint function is:

[0164]

[0165] in, It is the state of running from the outer line to the departure track; J t (R(S,s S ,h)*R(M',s M′ ,h),h) is the outer envelope R(S,s S ,h) and the departure field specific track R(M',s M′ ,h)Connectivity status; The time when the movement starts from the outer line to the departure track; Time to reach the track; n S is the number of outer wires; n M′ is the number of specific tracks; p is the number of the through train; n M′ is the number of through channels, s M′ ∈n M′ ; M' is the straight stock channel; n D is the number of tracks arriving at the site, s D ∈n D ;n S is the number of outer wires, s S ∈n S ; S is the outer cable.

[0166] Step S334. Construct a task completion status constraint function based on the number of through trains arriving at the arrival yard, the number of through trains running from the arrival yard to the outer line, the number of through trains running from the outer line to the departure yard, and the number of through trains;

[0167] Specifically, the transportation task completion constraint requires that in the coordination of the marshalling yard's transportation tasks and the skylight plan, it is necessary to ensure that all transportation tasks are completed and the economic benefits of the marshalling yard are ensured.

[0168]

[0169] in, The through train occupies the arrival track; It is the state for through trains to move from the arrival track to the outer track; It is the state of running from the outer line to the departure track; It is the state of through train running from the outer line to the departure track; m 3 is the number of through trains; T is the decision cycle; p is the number of the through train.

[0170] Step S335. The operation sequence constraint function, the resource capacity constraint function, the resource occupancy status constraint function, the task completion status constraint function and the even-numbered resource connection constraint function are used as constraint functions;

[0171] Specifically, all constraint functions are used as constraint functions to construct a multi-objective optimization model.

[0172] Step S34. constructing a multi-objective optimization model based on the first objective function, the second objective function and a plurality of constraint functions;

[0173] Specifically, the objective function and the constraint function together constitute a multi-objective optimization model.

[0174] Step S40. Based on the constraint functions preset in the multi-objective optimization model, the basic data is adjusted to obtain target data, where the target data is data that satisfies each constraint function in the multi-objective optimization model;

[0175] Specifically, step S40 specifically includes step S41, step S42, step S43, step S44 and step S45:

[0176] Step S41. According to the arrival time of the train at the marshaling yard, the time of the running route, the time of the arrival at the release line, the time of the disassembly completion, the number of tracks parked at the arrival yard, the selected route from the track at the arrival yard to the release line, and the order of the hump of the train, the chromosome is encoded with real numbers to obtain a first code;

[0177] Specifically, the present invention performs real number encoding on the chromosome of the solution train, and the encoding method of the chromosome of the solution train is as follows: Figure 2 As shown, among them, X0 is the arrival time of the arriving train at the marshaling yard, X1 is the time when the arriving train starts to move, X2 is the time when the arriving train arrives at the outer line, X3 is the time when the arriving train stops at the track at the arrival yard, X4 is the time when the arriving train moves from the track of the arrival yard to the outer line and selects the route, X5 is the time when the arriving train starts to move from the outer line to the departure yard, X6 is the time when the arriving train arrives at the corresponding track of the arrival yard, X7 is the time when the arriving train leaves the track, X8 is the time when the arriving train moves from the outer line to the track and selects the route, and X9 is the time when the arriving train stops at the track at the departure yard.

[0178] For further analysis of the chromosome of the through train, X0 is known and directly encoded into the corresponding data; X1 is the time when the train starts to move, and the specific data needs to be determined by the algorithm; since the train moving time is usually 3 minutes, and the train cannot be stopped once it starts moving, the value of X2 is 3 plus X1; X3 and X4 are also obtained by the algorithm; the occupancy of the corresponding tracks in the departure yard changes all the time, so the time when the through train moves from the outer line to the departure yard track needs to be obtained according to the algorithm, so the value of X5 is greater than or equal to X2 plus 3; the time for the train to move from the outer line to the departure yard track is 3 minutes, and the value of X6 is 3 plus X5; the time for the through train to perform technical operations on the corresponding tracks in the departure yard is 20 minutes, and the value of X7 is 20 plus X6; X8 and X9 are obtained by the algorithm.

[0179] Step S42. According to the order of the assembly start time, assembly end time, marshaling start time, marshaling completion time, the start time of the shunting yard track to the departure track, the technical operation start time, the technical operation completion time, the number of tracks parked in the shunting yard, the route selected from the shunting yard track to the departure track, and the number of tracks parked in the departure yard, the chromosome of the self-organized departure train is real-number encoded to obtain a second code;

[0180] Specifically, the present invention performs real number encoding on the chromosome of the self-compiled starting train, and the encoding method of the chromosome of the self-compiled starting train is as follows: Figure 3 , where Z0 is the parking time of the vehicle that first arrives at the marshaling yard track in the train marshaling content, that is, the assembly start time; Z1 is the parking time of the vehicle that last arrives at the marshaling yard track in the train marshaling content, that is, the assembly end time; Z2 is the start marshaling time, obtained by the algorithm; Z3 is the train marshaling completion time; Z4 is the time when the train starts to move from the marshaling yard track to the departure yard track; Z5 is the start time of departure technical operation; Z6 is the end time of departure technical operation; Z7 is the track where the vehicle is parked in the marshaling yard assembly; Z8 is the route selected by the train from the marshaling yard track to the departure yard track, and Z9 is the track where the train is parked in the departure yard.

[0181] For further analysis of the chromosome of the departure train, Z0 and Z1 are determined by the obtained train disassembly plan, and the corresponding data are selected for input; Z2 is the start time of marshaling, and the train starts marshaling when the vehicles required by the train are assembled. Therefore, the value of Z2 is greater than or equal to Z1, and the start time is obtained by the algorithm; since the train cannot be stopped once it starts marshaling and the time required for train marshaling is 20 minutes, the value of Z3 is 20 added to Z2; the value of Z4 is obtained by the algorithm; Z5 is the start time of departure technical operations, and the prerequisite for the start of technical operations is that the train arrives at the departure track, and the train travel time is 3 minutes, so the value of Z5 is greater than or equal to the value of Z4 plus 3; once the train departure technical operations begin, they cannot be stopped, and the time required for the train departure technical operations is 15 minutes, and the value of Z6 is 15 added to Z5; Z7, Z8, and Z9 are all obtained by the algorithm.

[0182] Step S43. According to the order of arrival time of the through train at the marshaling yard, start time of running route, arrival time of the outer line, arrival yard parking track, route selected from the arrival yard track to the outer line, start time of the outer line running to the departure yard track, arrival time of the arrival yard track, departure time of the arrival yard track, route selected from the outer line running to the departure yard track and number of parking tracks in the departure yard, real number encoding is performed on the chromosome of the through train to obtain a third encoding;

[0183] Specifically, Figure 4 As shown, the present invention performs real number encoding on the chromosome of the through train, wherein X0 is the time when the through train arrives at the marshaling yard, X1 is the time when the through train starts to move, X2 is the time when the through train arrives at the outer line, X3 is the time when the through train stops at the track at the arrival yard, X4 is the time when the through train moves from the track of the arrival yard to the outer line and selects the route, X5 is the time when the through train starts to move from the outer line to the departure yard, X6 is the time when the through train arrives at the corresponding track of the arrival yard, X7 is the time when the through train leaves the track, X8 is the time when the through train moves from the outer line to the track and selects the route, and X9 is the time when the through train stops at the track at the departure yard.

[0184] Further analysis of the chromosome of the through train shows that X0 is known and can be directly encoded into the corresponding data; X1 is the time when the through train starts to run, and the specific data needs to be determined by an algorithm. Under normal circumstances, the through train runs for 3 minutes, and once the through train starts running, the running route cannot be stopped. The value of X2 is 3 plus X1; X3 and X4 are also obtained by the algorithm; the occupancy of the corresponding tracks in the departure yard changes all the time, so the time for the through train to run from the outer line to the departure track needs to be obtained according to the algorithm, so the value of X5 is greater than or equal to X2 plus 3; the time for the through train to run from the outer line to the departure track is usually 3 minutes, and the value of X6 is 3 plus X5; the time for the through train to perform technical operations on the corresponding tracks in the departure yard is usually 20 minutes, and the value of X7 is 20 plus X6; X8 and X9 are also obtained by the algorithm.

[0185] Step S44. Optimize the first code, the second code, and the third code multiple times based on the genetic algorithm and a preset number of iterations. When the data corresponding to the optimized code satisfies the constraint function, calculate the objective function based on the optimized code to obtain multiple objective function values.

[0186] Step S45. Determine the minimum objective function value from the multiple objective function values, and use the data corresponding to the code corresponding to the minimum objective function value as the target data;

[0187] Specifically, an initial population with a population number of N is used, and the initial solution is determined according to the running order of the vehicle flow in the marshalling yard. The model of the present invention is a longitudinal marshalling system of the downlink system, so the running plans of the vehicle flow in the arrival yard, the shunting yard, and the departure yard are determined in sequence.

[0188] Perform the following operations on the population to generate a new generation of population:

[0189] Selection operation: construct a fitness function. The fitness function of the present invention is the inverse of the auxiliary function, which means that the larger the fitness value of an individual is, the smaller the corresponding objective function value is. That is, the shorter the time that all vehicles stay at the station in a certain scheme, the greater the probability of the scheme for the next generation. Roulette is used to eliminate the schemes with fitness crossing in the population. By comparing each individual with the sum of the fitness of all individuals, it is determined whether each individual enters the next generation. The fitness function is as follows:

[0190]

[0191] Among them, F(X j ) is the fitness function; f(x) is the objective function; α is the first penalty coefficient; β is the second penalty coefficient; h j (x) are the upper and lower bounds of the constraint; g i (x) is the constraint function;

[0192] Crossover operation: Since the total volume of vehicle flow in the marshalling yard is fixed, the total volume of vehicle flow of a chromosome is certain. Select the same position of two chromosomes, exchange different running plans of the same train, and then determine the feasibility and make feasibility adjustments to obtain a new transportation task.

[0193] Mutation operation: The mutation mode designed by the present invention is to complete the mutation operation for each chromosome independently. Since the values ​​of some gene positions in the train chromosome change with the changes of other gene positions, the gene positions that actually determine the expression form of the chromosome are not all the gene positions of the chromosome. For example, X1, X3, X4, X8, and X9 in the through train are determined by the algorithm, and the specific values ​​of the remaining gene positions can be obtained after the above gene positions are determined. Therefore, in the mutation, the chromosome mutation of the through train is a random position mutation in X1, X3, X4, X8, and X9, the chromosome mutation of the solution train is a random position mutation in Y1, Y4, Y5, and Y6, and the chromosome mutation of the self-compiled departure train is a random position mutation in Z2, Z4, Z7, Z8, and Z9.

[0194] When the maximum number of iterations set by the algorithm is reached, the algorithm terminates and determines the minimum objective function value from multiple objective functions. The result corresponding to the minimum objective function value is the output result.

[0195] Step S50. Adjust the train operation plan accordingly based on the target data;

[0196] Specifically, by solving the multi-objective optimization model, the train transportation tasks and skylight solutions of the marshalling yard are obtained, the traffic routes are optimized, and the operating efficiency of the marshalling yard and the skylight realization rate are improved.

[0197] Embodiment 2:

[0198] like Figure 5 As shown, this embodiment provides a train operation plan coordination optimization device, the device comprising:

[0199] A first obtaining unit 10 is used to divide the preset maintenance time into a plurality of skylights based on the vehicle flow of the marshalling yard to obtain a plurality of regional skylights;

[0200] An acquisition unit 20 is used to acquire basic data of a marshalling yard, wherein the basic data includes a train operation plan, all operations to be completed and corresponding time thresholds;

[0201] A second obtaining unit 30 is used to construct an optimization model based on the basic data and the multiple regional skylights to obtain a multi-objective optimization model, wherein the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function;

[0202] A first adjustment unit 40 is used to adjust the basic data based on the constraint functions preset in the multi-objective optimization model to obtain target data, where the target data is data that satisfies each constraint function in the multi-objective optimization model;

[0203] The second adjustment unit 50 is used to make corresponding adjustments to the train operation plan based on the target data.

[0204] In a specific implementation disclosed in the present application, the second obtaining unit 30 includes:

[0205] A first construction unit is used to construct a first objective function based on the occupation time of the arrival train in the regional skylight, the occupation time of the self-organized departure train in the regional skylight and the occupation time of the through train in the regional skylight;

[0206] The second construction unit is used to construct a second objective function based on the running time of the arriving and discharging trains at the marshaling yard, the running time of the self-organized and departing trains at the marshaling yard, and the running time of the through trains at the marshaling yard;

[0207] A third construction unit is used to construct multiple constraint functions based on basic data to obtain multiple constraint functions;

[0208] The fourth construction unit is used to construct a multi-objective optimization model based on the first objective function, the second objective function and multiple constraint functions.

[0209] In a specific embodiment disclosed in the present application, the first building block includes:

[0210] A third obtaining unit is used to obtain a first function based on the arrival field track occupation state, the push line occupation state and a first decision variable, wherein the first decision variable is used to characterize whether the approach corresponding to the arrival field track and the push line belongs to the regional skylight;

[0211] A fourth obtaining unit is used to obtain a second function based on the departure track occupation state, the release line occupation state and a second decision variable, wherein the second decision variable is used to characterize whether the approach corresponding to the departure track and the release line belongs to the regional skylight;

[0212] A fifth obtaining unit is used to obtain a third function based on the arrival field track occupation state, the outer line occupation state and the third decision variable, and the third decision variable is used to characterize whether the approach corresponding to the arrival field track and the outer line belongs to the regional skylight;

[0213] a sixth obtaining unit, configured to obtain a fourth function based on the occupation state of the departure yard through track, the occupation state of the outer line and a fourth decision variable, wherein the fourth decision variable is used to characterize whether the approach corresponding to the departure yard through track and the outer line belongs to the regional skylight;

[0214] The seventh obtaining unit is used to calculate the sum of the first function, the second function, the third function and the fourth function to obtain the first objective function.

[0215] In a specific embodiment disclosed in the present application, the second building block includes:

[0216] A first calculation unit is used to calculate the difference between the arrival time of each train at the marshaling yard and the disassembly completion time to obtain a plurality of fifth functions;

[0217] The second calculation unit is used to calculate the difference between the running time of each self-organized departure train and the time of leaving the marshaling yard to obtain multiple sixth functions;

[0218] A third calculation unit is used to calculate the difference between the arrival time and the departure time of each through train at the marshaling yard to obtain a plurality of seventh functions;

[0219] The fourth calculation unit is used to sum the multiple fifth functions, the multiple sixth functions and the multiple seventh functions to obtain the second objective function.

[0220] In a specific embodiment disclosed in the present application, the third building block includes:

[0221] A fifth construction unit is used to construct multiple operation constraint functions based on the operation logic of the arrival and departure trains, the operation logic of the self-compiled departure trains and the operation logic of the through trains;

[0222] A sixth construction unit is used to construct multiple resource capacity constraint functions based on the number of departure tracks, the number of arrival tracks, the dismantling and shunting capacity, the number of push lines, the number of release lines, the shunting yard capacity and the marshaling and shunting capacity;

[0223] A seventh construction unit is used to construct a resource connection constraint function and a resource occupancy state constraint function based on the connection state between the arrival track and the push line, the connection state between the release line and the departure track, the connection state between the arrival track and the outer line, and the connection state between the outer line and the departure track;

[0224] An eighth construction unit is used to construct a task completion state constraint function based on the number of through trains arriving at the arrival yard tracks, the number of through trains running from the arrival yard tracks to the outer line, the number of through trains running from the outer line to the departure yard tracks, and the number of through trains;

[0225] As a unit, it is used to use the job sequence constraint function, resource capacity constraint function, resource occupancy status constraint function, task completion status constraint function and even-numbered resource connection constraint function as constraint functions.

[0226] In a specific implementation disclosed in the present application, the first adjustment unit 40 includes:

[0227] The first encoding unit is used to perform real number encoding on the chromosome according to the arrival time of the marshaling yard, the running route time, the arrival time of the shunting line, the disassembly completion time, the number of parking tracks at the arrival yard, the selected route from the arrival yard track to the shunting line, and the order of the hump of the arrival and disassembly train to obtain a first code;

[0228] The second encoding unit is used to perform real number encoding on the chromosome of the self-organized originating train in the order of the assembly start time, assembly end time, marshaling start time, marshaling completion time, the start time of the movement from the shunting yard track to the departure yard track, the technical operation start time, the technical operation completion time, the number of tracks parked in the shunting yard, the route selected from the shunting yard track to the departure yard track, and the number of tracks parked in the departure yard, to obtain a second code;

[0229] According to the order of the through train's arrival time at the marshaling yard, the time of starting to run the route, the time of arriving at the outer line, the arrival yard parking track, the arrival yard track running to the outer line selected route, the outer line running to the departure yard track start time, the arrival yard track time, the departure yard track time, the outer line running to the departure yard track selected route and the number of parking tracks in the departure yard, the through train chromosome is real-number encoded to obtain the third code;

[0230] A third encoding unit is used to optimize the first encoding, the second encoding and the third encoding multiple times based on a genetic algorithm and a preset number of iterations, and when the data corresponding to the optimized encoding satisfies the constraint function, calculate the objective function based on the optimized encoding to obtain multiple objective function values;

[0231] The determination unit is used to determine the minimum objective function value from multiple objective function values, and use the data corresponding to the code corresponding to the minimum objective function value as the target data.

[0232] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0233] Embodiment 3:

[0234] Corresponding to the above method embodiment, this embodiment also provides a train operation plan coordination optimization device, and the train operation plan coordination optimization device described below and the train operation plan coordination optimization method described above can refer to each other.

[0235] Figure 3 FIG. 8 is a block diagram of a train operation plan coordination optimization device 800 according to an exemplary embodiment. Figure 3As shown, the train operation plan coordination and optimization device 800 may include: a processor 801 and a memory 802. The train operation plan coordination and optimization device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0236] Embodiment 4:

[0237] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the train operation plan coordination optimization method described above can refer to each other.

[0238] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0239] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for coordinating and optimizing a train operation plan, characterized in that: include: Based on the traffic volume of the marshalling yard, the preset maintenance time is divided into multiple skylights to obtain multiple regional skylights; Obtaining basic data of the marshalling yard, the basic data including the train operation plan, all operations to be completed and corresponding time thresholds; An optimization model is constructed based on the basic data and multiple regional skylights to obtain a multi-objective optimization model, wherein the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function; Based on the constraint functions preset in the multi-objective optimization model, the basic data is adjusted to obtain target data, where the target data is data that satisfies each constraint function in the multi-objective optimization model; The train operation plan is adjusted accordingly based on the target data.

2. The train operation plan coordination optimization method according to claim 1 is characterized in that , based on the basic data and multiple regional skylights, an optimization model is constructed to obtain a multi-objective optimization model, wherein the train operation plan includes an arrival train operation plan, a self-compiled departure train operation plan and a through train operation plan, including: Based on the occupation time of the arriving and departing trains in the regional skylight, the occupation time of the self-organized departure trains in the regional skylight and the occupation time of the through trains in the regional skylight, a first objective function is constructed; Constructing a second objective function based on the running time of the arriving and departing trains at the marshaling yard, the running time of the self-organized and departing trains at the marshaling yard, and the running time of the through trains at the marshaling yard; Constructing multiple constraint functions based on the basic data to obtain multiple constraint functions; The multi-objective optimization model is constructed based on the first objective function, the second objective function and multiple constraint functions.

3. The train operation plan coordination optimization method according to claim 2 is characterized in that: Based on the occupation time of the arrival and departure trains in the regional skylight, the occupation time of the self-organized departure trains in the regional skylight and the occupation time of the through trains in the regional skylight, a first objective function is constructed, wherein the train operation plan includes multiple routes, and the routes are represented by one or more of the arrival yard track occupation state, the push line occupation state, the release line occupation state, the departure yard track occupation state, the outer line occupation state and the departure yard through track occupation state, including: A first function is obtained based on the arrival field track occupation state, the push line occupation state and a first decision variable, wherein the first decision variable is used to characterize whether the approach corresponding to the arrival field track and the push line belongs to a regional skylight; A second function is obtained based on the occupation state of the departure track, the occupation state of the release line and a second decision variable, wherein the second decision variable is used to characterize whether the approach corresponding to the departure track and the release line belongs to a regional skylight; A third function is obtained based on the arrival field track occupation state, the outer line occupation state and a third decision variable, wherein the third decision variable is used to characterize whether the approach corresponding to the arrival field track and the outer line belongs to a regional skylight; A fourth function is obtained based on the occupation state of the departure yard through track, the occupation state of the outer line and a fourth decision variable, wherein the fourth decision variable is used to characterize whether the routes corresponding to the departure yard through track and the outer line belong to the regional skylight; The first objective function is obtained by summing up the first function, the second function, the third function and the fourth function.

4. The train operation plan coordination optimization method according to claim 3 is characterized in that , based on the running time of the arriving train at the marshaling yard, the running time of the self-organized departure train at the marshaling yard and the running time of the through train at the marshaling yard, a second objective function is constructed, including: Calculate the difference between the arrival time of each train at the marshaling yard and the disassembly completion time to obtain multiple fifth functions; Calculate the difference between the time of each self-organized departure train running on the route and the time of leaving the marshaling yard to obtain multiple sixth functions; Calculate the difference between the arrival time and departure time of each through train at the marshaling yard to obtain multiple seventh functions; The second objective function is obtained by summing up multiple fifth functions, multiple sixth functions and multiple seventh functions.

5. A train operation plan coordination and optimization device, characterized in that: include: A first obtaining unit is used to divide the preset maintenance time into a plurality of skylights based on the vehicle flow of the marshaling yard to obtain a plurality of regional skylights; An acquisition unit, used to acquire basic data of a marshalling yard, wherein the basic data includes a train operation plan, all operations to be completed and corresponding time thresholds; A second obtaining unit is used to construct an optimization model based on the basic data and multiple regional skylights to obtain a multi-objective optimization model, wherein the multi-objective optimization model includes multiple objective functions, and each basic data is used to construct at least one objective function; A first adjustment unit, configured to adjust the basic data based on a constraint function preset in the multi-objective optimization model to obtain target data, wherein the target data is data satisfying each constraint function in the multi-objective optimization model; The second adjustment unit is used to make corresponding adjustments to the train operation plan based on the target data.

6. The train operation plan coordination and optimization device according to claim 5, characterized in that: The second obtaining unit comprises: A first construction unit is used to construct a first objective function based on the occupation time of the arrival train in the regional skylight, the occupation time of the self-organized departure train in the regional skylight and the occupation time of the through train in the regional skylight; A second construction unit is used to construct a second objective function based on the running time of the arriving and departing trains at the marshaling yard, the running time of the self-organized and departing trains at the marshaling yard, and the running time of the through trains at the marshaling yard; A third construction unit is used to construct a plurality of constraint functions based on the basic data to obtain a plurality of constraint functions; The fourth construction unit is used to construct the multi-objective optimization model based on the first objective function, the second objective function and multiple constraint functions.

7. The train operation plan coordination and optimization device according to claim 6, characterized in that: The first building block comprises: a third obtaining unit, configured to obtain a first function based on the arrival field track occupation state, the push line occupation state and a first decision variable, wherein the first decision variable is used to characterize whether the approach corresponding to the arrival field track and the push line belongs to a regional skylight; a fourth obtaining unit, configured to obtain a second function based on the occupation state of the departure track, the occupation state of the release line, and a second decision variable, wherein the second decision variable is used to characterize whether the approach corresponding to the departure track and the release line belongs to a regional skylight; a fifth obtaining unit, configured to obtain a third function based on the arrival field track occupation state, the outer envelope line occupation state and a third decision variable, wherein the third decision variable is used to characterize whether the approach corresponding to the arrival field track and the outer envelope line belongs to a regional skylight; a sixth obtaining unit, configured to obtain a fourth function based on the occupation state of the departure yard through track, the occupation state of the outer line and a fourth decision variable, wherein the fourth decision variable is used to characterize whether the approach corresponding to the departure yard through track and the outer line belongs to a regional skylight; A seventh obtaining unit is used to sum the first function, the second function, the third function and the fourth function to obtain the first objective function.

8. The train operation plan coordination and optimization device according to claim 7, characterized in that: The second building block comprises: A first calculation unit is used to calculate the difference between the arrival time of each train at the marshaling yard and the disassembly completion time to obtain a plurality of fifth functions; The second calculation unit is used to calculate the difference between the running time of each self-organized departure train and the time of leaving the marshaling yard to obtain multiple sixth functions; A third calculation unit is used to calculate the difference between the arrival time and the departure time of each through train at the marshaling yard to obtain a plurality of seventh functions; The fourth calculation unit is used to sum up the multiple fifth functions, the multiple sixth functions and the multiple seventh functions to obtain the second objective function.

9. A train operation plan coordination and optimization device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the train operation plan coordination optimization method as described in any one of claims 1 to 4 when executing the computer program.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the train operation plan coordination optimization method as described in any one of claims 1 to 4.

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